If you feel your organization is a laggard with artificial intelligence, don’t feel bad — it turns out everyone else is struggling with it too. AI may be the talk of the town these days, but it’s only just getting out of the starting gate at most companies.
The question is, will AI remain in the labs while the industry moves on to the next technology trend, or will it become the revolutionary force some are predicting? Read More
Monthly Archives: January 2020
Autonomous Taxiing, Take-Off and Landing test flight
Hollywood is replacing artists with AI. Its future is bleak.
It took me an embarrassingly long time to realize that the “black mirror” of the popular anthology series Black Mirror was a screen, or rather, all the screens we surround ourselves with: phones, tablets, computers, TVs, and, increasingly, futuristic devices built by massive corporations that monitor our movements and preferences and words. We buy these black mirrors, welcoming them into our homes and lives and letting them — true to their name — reflect ourselves back to us. And as we know all too well, those reflections sometimes betray our darkest impulses.
Unsettling reflections are not the black mirrors’ fault. Gadgets are merely assemblages of wires and metal and glass. Devices don’t have a point of view; they operate according to the input they receive, the algorithms and designs and patterns that power the software, written by humans and thus shaded and slanted by human biases. Read More
The Four Components of Trusted Artificial Intelligence
Trust and transparency are at the forefront of conversations related to artificial intelligence(AI) these days. While we intuitively understand the idea of trusting AI agents, we are still trying to figure out the specific mechanics to translate trust and transparency into programmatic constructs. After all, what does trust means in the context of an AI system? Read More
Towards a Conversational Agent that Can Chat About…Anything
Modern conversational agents (chatbots) tend to be highly specialized — they perform well as long as users don’t stray too far from their expected usage. To better handle a wide variety of conversational topics, open-domain dialog research explores a complementary approach attempting to develop a chatbot that is not specialized but can still chat about virtually anything a user wants. Besides being a fascinating research problem, such a conversational agent could lead to many interesting applications, such as further humanizing computer interactions, improving foreign language practice, and making relatable interactive movie and videogame characters. Read More
Towards a Human-like Open-Domain Chatbot
We present Meena, a multi-turn open-domain chatbot trained end-to-end on data mined and filtered from public domain social media conversations. This 2.6B parameter neural net-work is trained to minimize perplexity, an automatic metric that we compare against human judgement of multi-turn conversation quality.To capture this judgement, we propose a human evaluation metric called Sensibleness and Specificity Average (SSA), which captures key elements of good conversation. Interestingly, our experiments show strong correlation between perplexity and SSA. The fact that the best perplexity end-to-end trained Meena scores high on SSA (72% on multi-turn evaluation) suggests that a human-level SSA of 86%is potentially within reach if we can better optimize perplexity. Additionally, the full version of Meena (with a filtering mechanism and tuned decoding) scores 79% SSA, 23% higher in absolute SSA than existing chatbots that we evaluated. Read More
Not to ML when your problem…
Essential Guide to AI Product Management
In this post when I use the term AI product management (APM), I mean to include both AI and ML (which is technically more accurate). I believe that AI PM is a key role and needs specific skills, judgement and experience that are critical to success of AI products and initiatives.
As a practicing APM and organizer of a successful AI Meetup, I wanted to share useful resources, best practices and tips that I came across and learned from my experience. The principles and tips here are also useful for project managers, software managers and any role where you make decisions for technology teams. I do not spend time talking about the basics of AI here as I assume you already have that background. However there are references at the end if you want to learn about ML or if you want to know more about PM role. Read More
MIT CSAIL: Introduction to Deep Learning
Google DeepMind’s ‘Sideways’ takes a page from computer architecture
Increasingly, machine learning forms of artificial intelligence are contending with the limits of computing hardware, and it’s causing scientists to rethink how they design neural networks.
That was clear in last week’s research offering from Google, called Reformer, which aimed to stuff a natural language program into a single graphics processing chip instead of eight. Read More
Rick's Cafe AI 